Abstract
Friction of each joint of a robot manipulator has to be effectively compensated for in order to realize precise position/force control of robot manipulators. Recently, soft computing techniques (fuzzy reasoning, neural networks, and genetic algorithm) have been playing an important role in the control of robots. Applying soft computing techniques, learning/adaptation ability and human knowledge can be incorporated into a robot controller. In this paper, we propose a two-stage adaptive robot manipulator position/force control method in which uncertain/unknown dynamic of the environment is compensated for in the task space and joint friction is effectively compensated for in the joint space using soft computing techniques. The effectiveness of the proposed control method was evaluated by experiments.
| Original language | English |
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| Pages | 141-144 |
| Number of pages | 4 |
| Publication status | Published - Dec 1 1999 |
| Externally published | Yes |
| Event | Proceedings of the 1999 3rd International Conference on Knowledge-Based Intelligent Information Engineering Systems (KES '99) - Adelaide, Aust Duration: Aug 31 1999 → Sept 1 1999 |
Other
| Other | Proceedings of the 1999 3rd International Conference on Knowledge-Based Intelligent Information Engineering Systems (KES '99) |
|---|---|
| City | Adelaide, Aust |
| Period | 8/31/99 → 9/1/99 |
ASJC Scopus subject areas
- Computer Science(all)